With the rise of services like Steam and Xbox Live, multiplayer support has become essential to the
success of many commercial video games. Explicit, server-client synchronisation models are bandwidth
intensive and error prone to implement, while implicit, peer-to-peer synchronisation models
are brittle, inflexible, and vulnerable to cheating. We present a generalised server-client network
synchronisation model targeted at complex games, such as real time strategy games, that previously
have only been feasible via peer-to-peer techniques. We use prediction, learning, and entropy coding
techniques to learn a bandwidth-efficient incremental game state representation while guaranteeing
both correctness of synchronised data and robustness in the face of unreliable network behavior. The
resulting algorithms are efficient enough to synchronise the state of real time strategy games such
as Blizzard’s Starcraft (which can involve hundreds of in-game characters) using less than three
kilobytes per second of bandwidth.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/1755 |
| Date | 06 1900 |
| Creators | Orsten, Sterling |
| Contributors | Buro, Michael (Computing Science), Ardakani, Masoud (Electrical and Computer Engineering), Nikolaidis, Ioanis (Computing Science) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 1188636 bytes, application/pdf |
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